Large-Scale Optimization with Applications
Concentration: Quantitative Methods
Optimization problems involving large numbers of variables or constraints arise frequently in problems concerning transportation policy, manpower and production planning, design of complex systems, logistics, data mining, and others. Furthermore, the number of variables often used to ensure a problem formulation is tractable (e.g., convex). Efficient algorithms are required to solve large-scale optimization problems since the number of computations grows by at least the cube of the number of variables or constraints. In this five-week advanced course, we will introduce students to efficient methods for formulating and solving large-scale optimization problems and describe applications where these problems may be encountered. In addition, we will introduce a heuristic method commonly employed to solve non-convex problems.